class_docstr: This class enables adjusting the momentum in batch normalization layer.
  
  .. note::
      It's an experimental feature and should be used with caution.
code: def adjust_momentum(
      self, model: nn.Module, iteration: int, epoch: int
  ) -> None:
      if iteration >= self.warmup_iterations:
          step = (
              iteration - self.warmup_iterations
              if self.is_iteration_based
              else epoch
          )
          curr_momentum = max(0.0, self.anneal_fn(step))
  
          for m in model.modules():
              if (
                  isinstance(m, (nn.BatchNorm2d, nn.SyncBatchNorm))
                  and m.training
              ):
                  m.momentum = curr_momentum
  
file_path: ml-cvnets/cvnets/layers/normalization_layers.py
imports: import math
  from torch import nn
  from cvnets.layers.normalization import NORM_LAYER_CLS, build_normalization_layer
  from utils import logger
label_desc: Use image node_id 4 for calling the AdjustBatchNormMomentum obj's underlying member method code with example usage: obj.adjust_momentum(model, iteration, epoch) without return types